We use different evaluation metrics to evaluate the performance of the models built in the experiments. These models are evaluated on the test sets using several evaluation metrics: BLEU [1]},
TER [2]} and METEOR [3]}. The scores assigned by this metrics indicate an estimation of the quality of the translation (compared to a human-translated reference). Higher scores of BLEU and METEOR indicate better translation quality. TER is an error metric, therefore lower scores indicate better performance.
